DC/DC变换器的变结构模糊控制研究

对不同类型的模糊PID控制器(模糊P控制器、模糊PD控制器、模糊PI控制器、模糊PID控制器)在DC/DC变换器中的应用作了全面的研究。目前,模糊PI控制器应用得最为广泛,然而在其控制作用下,DC/DC变换器的输出电压通常会超调,并且当响应时间较短时有很大的冲击电流尖峰。探讨一种变结构模糊控制器,这种控制器将有效地克服模糊PI控制器的上述不足。基于Matlab/Simulink对应用变结构模糊控制器控制的DC/DC变换器系统进行了计算机仿真。仿真结果表明,变结构模糊控制器控制拥有较好的动态特性和稳态性能。     

遗传算法优化的移相全桥变换器模糊PID控制

为解决常规PID控制难以应对移相全桥DC/DC变换器随时间变化非线性的问题,提出了一种基于遗传算法优化的模糊PID控制策略GA-FP。GA-FP通过模糊控制器调整PID的系数,应用遗传算法的全局寻优能力重新计算模糊PID控制器中的量化因子和比例因子,以提高控制响应速度,增强系统的鲁棒性。剖析了移相全桥变换器的电压闭环运行机制,设计了GA-FP的实现步骤,并采用MATLAB/Simulink进行仿真验证。仿真结果表明,GA-FP在稳定负载或负载突变时均可在0.5 ms内将输出电压稳定于48 V,调节速度快、超调量小,控制性能比没有优化的模糊PID和常规PID更好,且自适应能力更强。     

基于模糊PID控制的双向DC/DC变换器研究

双向DC/DC变换器是指在保持变换器两端的直流电压极性不变的情况下,根据实际需要完成能量双向传输的直流变换器。它在直流不间断电源系统、分布式电站、电动汽车以及太阳能电池阵中有广泛的应用。通过对双向半桥变换器的分析,并将其与蓄电池相结合使用,完成能量的双向传输和电池能量对电网的回馈。由于DC/DC变换器在升降压的过程中产生的严重的非线性问题,在控制方案上,采用模糊PID控制的电压、电流双闭环控制。仿真表明,与传统的PID控制相比,该控制方案有效提高了变换器的鲁棒性,减小输出电压波动,能够实现能量的双向流动。     

DC／DC变换单神经元自适应PID控制器仿真研究

为解决传统PI控制对具有时变、非线性特性的DC/DC变换器动态控制性能不佳的问题,将人工神经网络与PID控制理论相结合,为DC/DC变换器设计了一种单神经元自适应PID控制器。该控制器算法简单,通过对加权系数的在线调整来实现自适应、自学习功能,从而满足DC/DC变换器的时变及非线性特性。以BUCK型变换器为例,建立了DC/DC变换器智能控制系统的仿真模型,在不同负载及参数变化的情况下与常规PI控制效果进行对比分析,结果表明,单神经元自适应PID控制器对DC/DC变换器具有很好的控制效果和鲁棒性。     

Z源逆变器的模糊PID电路控制系统设计

设计一种基于模糊PID的控制器,用于Z源逆变器输出电压的控制。模糊PID控制器结构简单,性能优良。通过仿真分析和试验验证,证明该控制器对负载和输入电压突变具有一定的抗干扰能力,能保证Z源逆变器输出电压的稳定性。     

模糊PID控制在底盘测功机中的应用研究

底盘测功机是一个复杂的时变非线性、大惯性系统,传统的PID控制对于非线性、时变性的系统难以达到控制精度的要求,而模糊PID控制具有在线自动调整的功能,从对传统的PID与模糊PID比较的基础上。分析了参数对系统性能的影响,并利用MATLAB软件中的模糊工具箱对连续系统进行了仿真,仿真结果表明,模糊PID控制器具有良好的跟踪性能,超调量小、控制精度高、调节速度快,可以实现对PID参数的最佳调整。     

自适应人工神经网络电机控制器设计

提出了一种自适应人工神经网络无刷直流电动机(BLDCM)转速控制器设计方法;针对传统PID调节器难以应对系统超调和短时振荡等问题,提出了一种结合人工神经网络和传统PID控制的新方法;首先建立了(BLDCM)的本体数学模型,在此基础上描述了将人工神经网络和PID控制相结合的模型,并对具体的控制算法进行了定义;最后,使用Matlab仿真工具对BLDCM控制实例进行了仿真;实验结果表明,结合人工神经网络和PID控制器的新控制方法具有响应快、鲁棒性强以及控制精度高等优点,很好地抑制了超调和振荡。     

模糊预补偿PID控制

利用模糊控制理论的非线性特性，在工业过程控制中将其与PID控制结合，能改善常规PID控制器的控制性能。给出了一种基于模糊逻辑规则作为预补偿机制的PID控制。采用模糊推理和改进Z—N方法结合的方法。通过使用模糊逻辑规则作为预补偿器调整控制信号。校正PID控制器产生的较大超调，以达到改善PID控制器控制性能的目的。经仿真证明。该方法可克服传统Z—N方法产生的过大超调和较长调整时间的不足，同时又保持较好的抗负荷扰动能力和鲁棒性。     

电子束快速成型温度自适应模糊PID控制系统

将自适应模糊PID控制技术应用于电子束快速成型温度控制系统中,通过温度采集装置实时得到被加工件的温度信号,与设定值进行对比从而得到温度偏差及偏差的变化率,将温度偏差及偏差的变化率作为模糊控制器的2个输入变量,以自适应模糊PID控制器输出控制量调节电子束流大小,实现电子束快速成型温度的闭环控制.仿真结果表明,该控制系统具有调整时间短、稳态误差小、超调量小,即在电子束快速成型过程中,采用自适应模糊PID控制器比采用传统的PID控制器或模糊控制器可以得到更好的动态响应性能和控制精度.     

基于模糊PID的静变电源控制技术研究

为提高静变电源输出电压的质量,研究了一种自整定模糊PID控制方法。该方法将模糊控制优良的动态性能、灵活的控制特性和PID稳态控制性能的优势相结合,实时地对系统控制量进行调整。在Matlab/Simulink环境下,对于模糊PID和常规PID在静变电源控制中的应用分别进行了仿真。仿真结果表明,模糊PID控制器减少了超调量,抗干扰性和鲁棒性强,系统的动态、稳态性能得到了很大程度的提高。     

Application of Fuzzy Logic Controlled Cathodic Protection on Iraq-Turkey Crude Oil Pipeline

Impressed current cathodic protection is widely used to prevent corrosion of structural steels. The major constituents, which accelerate corrosion, are resistivity, chlorides, sulfatesand the acidity (pH) of the soil. Because of these variations, the transformer-rectifier units must control and tune the output voltage depending on desired reference voltage steadily. Usually, classical controls such as PI and PID, have been widely used with their gains manually tuned based on the desired reference voltage. But, classical controls require different gains at the lower and higher end of the output voltage range to avoid overshoot and oscillation. In this study, a closed loop control system incorporating fuzzy logic has been developed for tuning output voltage of the transformer-rectifier units. The algorithm based on fuzzy logic was implemented on a modern microcontroller (PIC16F877) allowing great flexibility for various real time applications. The desired reference voltage has been given by using keypad and output values have been displayed on an LCD. It is achieved by implementing an adaptation mechanism based on fuzzy logic controller to compensate for the variations and the dynamic changes in the environment. The proposed fuzzy logic controller was applied to two different areas on Iraq-Turkey crude oil pipeline. When the performance of the proposed fuzzy logic controller was observed, it has been seen that the output voltage of transformer-rectifier unit controlled by fuzzy logic controller has no overshoot and oscillation in the both areas.     

Fuzzy PWM based on Genetic Algorithm for battery charging

This paper investigates the use of fuzzy logic control together with Genetic Algorithm (GA) to tune corresponding membership functions in a pulse width modulation voltage (PWM)-based converter for battery charging. For quick charging purposes, a current-charging mode is built on the charging battery series with small impedance resistance. Once the rechargeable battery voltage reaches the preset output voltage value during the current-charging mode, constant voltage-charging mode should take to do the battery charging. No matter what you use a voltage/current mode for battery charging, the PWM converter with tuning duty cycle is necessary to obtain various output voltages to charge battery. The proposed pulse width modulation (PWM) control strategy based on fuzzy logic systems is applied to charge batteries for buck converter. A simulation is proposed to illustrate the efficiency of the design proposed in this paper.     

Maximum power tracking of a generic photovoltaic system via a fuzzy controller and a two-stage DC–DC converter

This study presents a new two-stage DC–DC converter for maximum power point tracking (MPPT) and a voltage boost of a generic photovoltaic (PV) system. An intelligent MPPT of PV system based on fuzzy logic control (FLC) is presented to adaptively design the proposed fuzzy controlled MPPT controller (FC-MPPTC) while a voltage boost controller (VBC) is used to fix the output voltage to a voltage level that is higher than the required operating voltage to the back-end grid impedance. Modeling and simulation on the PV system and the DC–DC converter circuit are achieved by state-space and the software Powersim. The PV string considered has the rated power around 600?VA under varied partial shadings. The FC-MPPTC and VBC are designed and realized by a DSP module (TMS320F2812) to adjust the duty cycle in the two-stage DC–DC converter. A special FLC algorithm is forged to render an MPPT faster and more accurate than conventional MPPT technique, perturb and observe (P&O). The simulations are intended to validate the performance of the proposed FC-MPPTC. Experiments are conducted and results show that MPPT can be achieved in a fast pace and the efficiency reaches over 90?%, even up to 96?%. It is also found that the optimized tracking speed of the proposed FC-MPPTC is in fact more stable and faster than the general P&O method with the boost voltage capable of offering a stable DC output.     

DC-DC变换器数字PID控制算法设计和修正

本文以Buck(降压型)DC—DC交换器为例，提出了对数字PWM的PID控制器的两种修正方式：死区控制方式，平均数字滤波控制方式。数字控制器根据输出电压误差决定是否用该修正方式计算下一个占空此。对系统的测试说明经过修正的PID控制buck型DC—DC交换器可以同时得到稳定精确的稳态响应和快速的瞬态响应。     

Smart hanger dynamic modeling and fuzzy controller design

The controlled smart hanger is an indispensable component in the automatic system for garment inspection. Fuzzy logic is chosen for the smart hanger manipulator since it can describe the human behavior remarkably well. In this paper, the dynamic model of the manipulator governing the contact force with garment fabric is first developed. An adaptive fuzzy logic PID control scheme is successfully formulated for the contact force control. Simulation results indicate that the fuzzy PID controller can yield a faster response without overshoot and a smaller error performance as compared to the traditional method based on PID. The stability of the fuzzy PID controller is also demonstrated by computer simulations.     

无刷直流电机的模糊神经网络控制设计

在无刷直流电机(BLDCM)的控制上,传统PID等控制方法存在或多或少的不足.在模糊PID控制的基础上提出了一种模糊神经网络PI控制器的设计方法.该方法结合了模糊逻辑与神经网络,使得模糊控制器模拟了人的控制功能,不仅对环境变化有较强的适应能力,还拥有自学习能力.相比模糊PID控制,其具有计算量小、稳定性强等特点.对BLDCM进行建模与分析;在BLDCM数学模型的基础上,分别设计模糊PID控制器和模糊神经网络PI控制器;对设计的控制器进行仿真验证并分析.实验结果表明,模糊神经网络PI控制具有跟踪性能好、超调小、响应快、脉动小等优点,其动静态特性均优于模糊PID控制.     

基于半导体制冷片的超速离心机温度控制模块设计

设计了超速离心机的温度控制模块,采用了模糊PID算法,通过PID参数的自动整定,对半导体制冷片的电压进行调整,从而控制半导体制冷片的制冷或制热效率,能对超速离心机离心室内的温度进行精确并且快速的控制.在MATLAB的simulink环境下进行仿真后分析可知,模糊PID算法兼具常规PID算法和模糊控制的优点,能够有效提高...     

A type-2 fuzzy logic controller design for buck and boost DC–DC converters

Conventional (type-1) fuzzy logic controllers have been commonly used in various power converter applications. Generally, in these controllers, the experience and knowledge of human experts are needed to decide parameters associated with the rule base and membership functions. The rule base and the membership function parameters may often mean different things to different experts. This may cause rule uncertainty problems. Consequently, the performance of the controlled system, which is controlled with type-1 fuzzy logic controller, is undesirably affected. In this study, a type-2 fuzzy logic controller is proposed for the control of buck and boost DC–DC converters. To examine and analysis the effects of the proposed controller on the system performance, both converters are also controlled using the PI controller and conventional fuzzy logic controller. The settling time, the overshoot, the steady state error and the transient response of the converters under the load and input voltage changes are used as the performance criteria for the evaluation of the controller performance. Simulation results show that buck and boost converters controlled by type-2 fuzzy logic controller have better performance than the buck and boost converters controlled by type-1 fuzzy logic controller and PI controller.     

基于改进模糊PI控制的双有源桥DC-DC变换器

在直流微电网中,针对直流负载扰动的过程会造成直流电压动态响应速度缓慢;同时,负荷投切时会引起直流电压超调量大的问题。采用改进模糊PI控制,并将其应用在直流微电网中储能单元的双有源桥DC-DC变换器。首先,在现有模糊PI控制中加入预处理环节,该环节对直流电压的误差大小进行及时判断与跟踪,使直流母线电压迅速达到参考值,提高了直流电压的动态响应速度;其次,分析了现有模糊PI控制算法的规则表对参数调节过程中存在精确度不足的规则,对其进行修改得到改进模糊PI控制的规则表,以减小直流电压的超调量;最后,对所提的改进模糊PI控制进行仿真对比验证。仿真结果表明:对现有的PI控制器和模糊PI控制器而言,改进的模糊PI控制器在稳态响应速度、超调量以及抗干扰性能上得到显著提高,提高了直流母线电压质量。